Identify vulnerabilities, assess security posture, and mitigate risks in your AI systems with comprehensive audits from model training through production deployment.
Recent studies show that the majority of production AI systems contain at least one critical security vulnerability. Without regular audits, organizations remain unaware of data poisoning risks, model extraction vulnerabilities, adversarial attack surfaces, and compliance gaps until a breach occurs.
Uncover hidden attack vectors in data pipelines, model architectures, APIs, and deployment infrastructure before attackers exploit them.
Identify areas of non-compliance with GDPR, HIPAA, SOC 2, and emerging AI regulations before costly audits or penalties.
Get actionable risk assessments with severity ratings and remediation roadmaps prioritized by business impact.
We begin with comprehensive discovery to understand your AI landscape and define audit scope:
Deep technical analysis of your AI systems for security vulnerabilities and weaknesses:
Active security testing simulating real-world attack scenarios:
Evaluate compliance with regulatory requirements and industry standards:
Deliver actionable findings with clear prioritization and implementation guidance:
Detailed 50-100 page report documenting all findings, technical analysis, compliance gaps, and remediation recommendations with visual diagrams and evidence.
Interactive dashboard showing risk scores across categories, trend analysis, and progress tracking for remediation efforts.
Prioritized action plan with timelines, resource requirements, and step-by-step implementation guidance for each finding.
Board-ready presentation summarizing key risks, business impact, and recommended investments for stakeholder communication.
Reference implementations, security testing scripts, and code examples demonstrating secure AI development practices.
30-day post-audit support for questions, implementation guidance, and validation of remediation efforts.
Schedule a comprehensive AI security audit and get actionable insights to protect your systems.
Audit duration depends on scope and complexity. A focused audit of a single AI system typically takes 2-3 weeks (discovery, testing, and reporting). Comprehensive audits covering multiple models, full ML pipelines, and compliance frameworks range from 4-8 weeks. We provide a detailed timeline after initial scoping. Express audits (1 week) are available for specific security concerns or pre-deployment validation.
We design audits to minimize operational impact. Most testing occurs in staging environments or uses read-only access to production. When production testing is necessary (API security, monitoring), we coordinate during low-traffic windows and implement rate limiting. Our methodology prioritizes non-invasive assessment techniques, with any potentially disruptive tests requiring explicit approval and scheduling.
AI audits address unique attack surfaces absent in traditional systems: adversarial attacks on model inference, data poisoning in training pipelines, model extraction through API queries, bias and fairness concerns with regulatory implications, and ML-specific compliance requirements (EU AI Act, algorithmic accountability). We combine traditional infrastructure security assessment with specialized AI/ML security expertise, including adversarial testing, model robustness evaluation, and data lineage analysis.
We offer both audit and remediation services. Our standard audit includes detailed remediation recommendations with implementation guidance. For clients who want hands-on support, we provide optional remediation implementation services including security control deployment, code fixes and architectural changes, compliance framework implementation, and security monitoring setup. We can also train your team on secure AI development practices to prevent future vulnerabilities.
We recommend annual comprehensive audits as a baseline, with additional audits triggered by significant changes: deployment of new high-risk AI systems, major model updates or retraining, infrastructure migrations or architectural changes, regulatory requirement changes, or after security incidents. For high-risk applications (healthcare, finance, autonomous systems), quarterly focused audits provide better continuous assurance. We also offer continuous security monitoring services between formal audits.
Comprehensive security for your entire machine learning infrastructure.
Protect your models from adversarial manipulation and attacks.
Safeguard your proprietary models from theft and unauthorized use.
Ensure your AI systems meet regulatory requirements and standards.
Don't wait for a security breach. Get a comprehensive AI security audit and risk assessment from Boaweb AI's expert team.
Based in Lund, Sweden | Serving clients globally |